We talked to TRA Manager Dr. Daniel Minge, who gave some interesting insights into the TRA Modelling and its offers.
Could you share what you consider to be the most pressing topics or challenges currently addressed within the TRA?
The research profile of TRA Modelling deliberately addresses a broad, open spectrum of inter-/transdisciplinary topics that are understood as “application fields” of the core disciplines of Applied Mathematics and Computer Science, the basis for modeling approaches. The overarching challenge of TRA Modelling is describing the interaction of numerous individual factors in complex systems with accurate models, predicting complex systems in simulations and, ultimately, yielding a real understanding of how those complex systems actually work. Since the launch of the TRA in 2020, this open concept has been filled with life by our TRA members. They approached TRA Modelling with project ideas and thereby helped to develop and form new application fields, in particular Economics, Geoscience and Life Sciences & Medicine.
How many members are involved in the TRA and what subject areas do they represent?
TRA Modelling is a research network at the interface of Applied Mathematics and Computer Science but it addresses diverse application fields. This versatility offers the opportunity for more intensive cooperation in many topics in which modeling approaches play a pivotal role. Therefore, the scientific community behind TRA Modelling got more and more heterogeneous. Today, 37 % of our 164 members are based outside of the Faculty of Mathematics and Natural Sciences, which as such is already home to a broad spectrum of departments. We roughly categorize our TRA members according to their main research priority of Mathematics (29%), Computer Science (21%), Economics (6%), Medicine & Life Sciences (21%), Geoscience & Agriculture (13%), Physics & Chemistry (4%) and other (5%).
What makes the TRA particularly interesting for early-career researchers, and how might they benefit from being involved?
The TRA offers events for specific occasions, such as lectures or network meetings, which are generally also open to doctoral students. In our announcements, we encourage PIs to pass on the information within their working group. Some TRA events are explicitly for young scientists, such as a hands-on workshop for machine learning in 2024. However, it is only fair to note that the TRA is not primarily aimed at doctoral students. The TRA is intended as a platform for networking beyond the boundaries of one's own discipline. In the early doctoral phase, this usually plays a minor role, as the deepening within a discipline has just begun. A broader view might become useful for PhD students in a later phase. Doctoral students can apply for TRA membership if they are very interested but they are not eligible to apply for TRA funding. The reason for this is that the ability to carry out independent scientific work must be given. Most of our members therefore have a professorship or a doctorate. Of course, doctoral students can also benefit indirectly if they are working on a project for which the PI has received seed funding from the TRA.
If early-career researchers would like to learn more about the TRA and how to join, when and where can they meet you directly?
If there are questions that are not answered by our homepage, do not hesitate to just contact us. As mentioned, TRA events would be the most beneficial offer for PhD candidates. We endeavor to advertise the events beyond our own mailing list, depending on the objective and theme of the event. All upcoming events in which TRA Modelling is involved are summarized in a separate section on our homepage. This is the easiest way to find out about the scope of an event and what to expect from it.